---
license: apache-2.0
base_model: facebook/deit-tiny-patch16-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: smids_1x_deit_tiny_adamax_001_fold4
  results:
  - task:
      name: Image Classification
      type: image-classification
    dataset:
      name: imagefolder
      type: imagefolder
      config: default
      split: test
      args: default
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.84
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# smids_1x_deit_tiny_adamax_001_fold4

This model is a fine-tuned version of [facebook/deit-tiny-patch16-224](https://huggingface.co/facebook/deit-tiny-patch16-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 1.6471
- Accuracy: 0.84

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

More information needed

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 0.001
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 50

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.7464        | 1.0   | 75   | 0.5642          | 0.795    |
| 0.5514        | 2.0   | 150  | 0.5108          | 0.8017   |
| 0.3856        | 3.0   | 225  | 0.5385          | 0.8033   |
| 0.4541        | 4.0   | 300  | 0.4488          | 0.825    |
| 0.4047        | 5.0   | 375  | 0.4448          | 0.815    |
| 0.2699        | 6.0   | 450  | 0.5321          | 0.8267   |
| 0.3444        | 7.0   | 525  | 0.4477          | 0.8367   |
| 0.1984        | 8.0   | 600  | 0.5491          | 0.81     |
| 0.1797        | 9.0   | 675  | 0.7263          | 0.8167   |
| 0.1145        | 10.0  | 750  | 0.6218          | 0.8317   |
| 0.1353        | 11.0  | 825  | 0.7800          | 0.8183   |
| 0.1658        | 12.0  | 900  | 0.6252          | 0.835    |
| 0.101         | 13.0  | 975  | 0.8640          | 0.805    |
| 0.0897        | 14.0  | 1050 | 0.9357          | 0.8      |
| 0.0267        | 15.0  | 1125 | 1.0487          | 0.8283   |
| 0.0597        | 16.0  | 1200 | 1.0545          | 0.8283   |
| 0.0984        | 17.0  | 1275 | 0.9221          | 0.83     |
| 0.0994        | 18.0  | 1350 | 0.9468          | 0.8367   |
| 0.0261        | 19.0  | 1425 | 1.1404          | 0.8117   |
| 0.0439        | 20.0  | 1500 | 1.1737          | 0.8233   |
| 0.0258        | 21.0  | 1575 | 1.1898          | 0.8383   |
| 0.0027        | 22.0  | 1650 | 1.4604          | 0.8217   |
| 0.0296        | 23.0  | 1725 | 1.3681          | 0.8267   |
| 0.004         | 24.0  | 1800 | 1.5826          | 0.83     |
| 0.0296        | 25.0  | 1875 | 1.2731          | 0.8167   |
| 0.0022        | 26.0  | 1950 | 1.4166          | 0.83     |
| 0.0213        | 27.0  | 2025 | 1.3755          | 0.8433   |
| 0.0191        | 28.0  | 2100 | 1.6417          | 0.82     |
| 0.0068        | 29.0  | 2175 | 1.3938          | 0.8417   |
| 0.0003        | 30.0  | 2250 | 1.4213          | 0.8317   |
| 0.0002        | 31.0  | 2325 | 1.4622          | 0.8417   |
| 0.0           | 32.0  | 2400 | 1.5110          | 0.8367   |
| 0.0291        | 33.0  | 2475 | 1.4845          | 0.8383   |
| 0.0005        | 34.0  | 2550 | 1.5757          | 0.8333   |
| 0.0089        | 35.0  | 2625 | 1.6525          | 0.83     |
| 0.0053        | 36.0  | 2700 | 1.6166          | 0.84     |
| 0.0078        | 37.0  | 2775 | 1.5899          | 0.8467   |
| 0.0           | 38.0  | 2850 | 1.6250          | 0.8433   |
| 0.0004        | 39.0  | 2925 | 1.6311          | 0.8433   |
| 0.0           | 40.0  | 3000 | 1.6268          | 0.8433   |
| 0.0032        | 41.0  | 3075 | 1.6310          | 0.8417   |
| 0.0           | 42.0  | 3150 | 1.6322          | 0.84     |
| 0.0           | 43.0  | 3225 | 1.6387          | 0.84     |
| 0.0           | 44.0  | 3300 | 1.6405          | 0.84     |
| 0.0           | 45.0  | 3375 | 1.6426          | 0.84     |
| 0.0           | 46.0  | 3450 | 1.6435          | 0.84     |
| 0.0           | 47.0  | 3525 | 1.6443          | 0.84     |
| 0.0           | 48.0  | 3600 | 1.6452          | 0.84     |
| 0.0           | 49.0  | 3675 | 1.6465          | 0.84     |
| 0.0           | 50.0  | 3750 | 1.6471          | 0.84     |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0